Pub. Date:
Springer International Publishing
Advances in Feature Selection for Data and Pattern Recognition

Advances in Feature Selection for Data and Pattern Recognition

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This book presents recent developments and research trends in the field of featureselection for data and pattern recognition, highlighting a number of latest advances.

The field of feature selection is evolving constantly, providing numerous newalgorithms, new solutions, and new applications. Some of the advances presentedfocus on theoretical approaches, introducing novel propositions highlighting anddiscussing properties of objects, and analysing the intricacies of processes and boundson computational complexity, while others are dedicated to the specific requirementsof application domains or the particularities of tasks waiting to be solved or improved.

Divided into four parts – nature and representation of data; ranking and exploration offeatures; image, shape, motion, and audio detection and recognition; decision supportsystems, it is of great interest to a large section of researchers including students,professors and practitioners.

Product Details

ISBN-13: 9783319675879
Publisher: Springer International Publishing
Publication date: 11/17/2017
Series: Intelligent Systems Reference Library , #138
Edition description: 1st ed. 2018
Pages: 328
Product dimensions: 6.10(w) x 9.25(h) x (d)

Table of Contents

An Introduction.- Attribute Selection Based on Reduction of Numerical Attribute During Discretization.- Improving Bagging Ensembles for Class Imbalanced Data by Active Learning.- Optimization of Decision Rules Relative to Length Based on Modified Dynamic Programming Approach.- Ranking-Based Rule Classifier Optimisation.- Attribute Selection in a Dispersed Decision-Making System.- Feature Selection Approach for Rule-based Knowledge Bases.- Feature Selection with a Genetic Algorithm for Classification of Brain Imaging Data.

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